perform_t_test: Welch Two-Sample t-Test for Differential Gene Expression

In DGEAR: Differential Gene Expression Analysis with R

Welch Two-Sample t-Test for Differential Gene Expression

Description

Performs an independent two-sample Welch t-test for every gene (row) in the expression matrix, applies Benjamini-Hochberg (BH) correction, and returns a results table together with the list of significant DEGs.

Usage

perform_t_test(
  dataframe,
  con1,
  con2,
  exp1,
  exp2,
  alpha = 0.05,
  annot_df = NULL
)

Arguments

dataframe	A numeric matrix or data.frame of gene expression values (rows = genes, columns = samples). Values are automatically log2- transformed when they appear to be on a linear / intensity scale.
con1	Integer. Index of the first control column.
con2	Integer. Index of the last control column.
exp1	Integer. Index of the first experiment column.
exp2	Integer. Index of the last experiment column.
alpha	Numeric significance threshold for BH-adjusted p-values (default 0.05).
annot_df	Optional annotation data.frame with columns ID and Gene.Symbol (or Gene.symbol). When NULL (default) row names of dataframe are used as gene identifiers.

Value

A named list:

Table

Data.frame with columns G_Symbol, log2FC, statistic.t, p.value, BH, fdr.

DEGs

Data.frame of gene identifiers whose BH-adjusted p-value is \le alpha.

Examples

library(DGEAR)
data("gene_exp_data")
result <- perform_t_test(dataframe = gene_exp_data,
                         con1 = 1, con2 = 10,
                         exp1 = 11, exp2 = 20)
head(result$Table)
result$DEGs

DGEAR documentation built on July 3, 2026, 9:07 a.m.